OpenDataLab @OpenDataLab_AI

Joined February 2023

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OpenDataLab @OpenDataLab_AI

2 days ago

🚀 The MinerU2.5 Technical Report is officially released!

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OpenDataLab @OpenDataLab_AI

2 months ago

@mrbleem_eth MinerU是上海AI 实验室的哦，如果觉得vlm慢，可以使用Sglang加速，快到起飞。当然，这对设备有一定性能要求和门槛

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#MathFusion is a novel framework that enhances mathematical reasoning through cross-problem instruction synthesis. 🦾Experimental results demonstrate that it achieves substantial improvements in mathematical reasoning while maintaining high data efficiency. #AI #Datasets

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OpenDataLab @OpenDataLab_AI

3 months ago

Vis3 is a visualization tool for #LLM and machine learning data, supporting cloud storage platforms with S3 protocol and various data formats. It offers interactive visualization through JSON, HTML, Markdown, and image views for efficient #data analysis.

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OpenDataLab @OpenDataLab_AI

4 months ago

#MinerU has officially cooperated with @CherryStudioHQ. You can directly call the MinerU function in Cherry Studio. MinerU officially provides each Cherry Studio user with a document processing quota of up to 500 pages per day.

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OpenDataLab @OpenDataLab_AI

4 months ago

#LabelLLM introduces an open-source platform dedicated to optimizing the #data annotation process integral to the development of #LLM. There are key features of LabelLLM. Try me👉 labelu-llm-demo.shlab.tech/supplier/task

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OpenDataLab @OpenDataLab_AI

4 months ago

#MinerU leverages the sophisticated PDF-Extract-Kit models to extract content from diverse documents effectively and ensure the accuracy of the final results. As its core, MinerU commits to facilitating the #mathematical and extended formulas parsing.

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Andrew Ng @AndrewYNg

4 months ago

Agentic Document Extraction just got much faster! From previous 135sec median processing time down to 8sec. Extracts not just text but diagrams, charts, and form fields from PDFs to give LLM-ready output. Please see the video for details and some application ideas.

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OpenDataLab @OpenDataLab_AI

4 months ago

The open-source dataset WanJuanSiLu, designed to provide high-quality training corpora for low-resource languages, thereby advancing the research and development of multilingual models. WanJuanSiLu mainly consists of eight subsets: Thai, Russian, Arabic, Korean, Hungarian, etc.

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OpenDataLab @OpenDataLab_AI

4 months ago

Based on the Classification System, we divided #WanJuanSiLu into 7 major categories, covering a wide range of content with characteristics of the language's geographic location, such as #history, #politics, #culture, #shopping, #encyclopedic knowledge. huggingface.co/datasets/opend…

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OpenDataLab @OpenDataLab_AI

5 months ago

We are very pleased to know that one of our users just launched a website about #MinerU! The website has deployed open-source solutions for data processing, tutoring, sharing of usage experience, etc. Welcome to join the community : mineru.site

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OpenDataLab @OpenDataLab_AI

5 months ago

Document content analysis has been a crucial research area in computer vision. We present #MinerU, an open-source solution for high-precision document content extraction. Deep dive into MinerU via the technical report: mineru.site/Saaas%E6%9C%8D…